The Interface
Deep television libraries contain buried value that is hard for digital teams to access quickly and effectively.
Most AI search tools use vector search, which summarizes data before indexing it and produces irrelevant, vague, or low-value results that rarely translate into usable content.
Visual search is another approach. It identifies what the camera sees, not necessarily what actually happened. Useful for occasional edge cases, but not built to thoroughly mine for meaningful content.
ClipMiner scans your entire library of broadcast caption files or transcripts, one theme at a time, and surfaces moments with the granularity production actually requires. Exact dialogue, full context, no stone left unturned.
Transcripts can be sourced automatically from YouTube and other platforms. Built on content your production already has. No new infrastructure.
Caption files
Episode metadata
Production notes
Full archive scan
No compression
Private search
Specific moments
Full context
Production-ready
Digital teams working inside long-running formats like game shows, court, talk, soaps, and reality, where the archive has real value and accessing it is the bottleneck.
Built by producers for producers. We have spent years inside deep television libraries finding moments and turning them into digital content that performs. We built the tool we always needed.
Your content is never stored or used for training. Queries are processed in real time through enterprise-grade AI providers and nothing is retained after each request.
ClipMiner does not index, summarize, or hold your archive. Your files stay under your control at all times.
If this resonates, we should talk.